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Migdalas, AthanasiosORCID iD iconorcid.org/0000-0001-8473-3663
Publications (10 of 115) Show all publications
Marinakis, Y., Marinaki, M. & Migdalas, A. (2018). Particle Swarm Optimization for the Vehicle Routing Problem: A Survey and a Comparative Analysis. In: Rafael Martí, Pardalos Panos, Dr. Mauricio G. C. Resende (Ed.), Handbook of Heuristics: . Paper presented at Conference LOT 2014 : Logistics, optimization and transportation 01/09/2014 - 02/09/2014 (pp. 1-34). Paper presented at Conference LOT 2014 : Logistics, optimization and transportation 01/09/2014 - 02/09/2014. Springer
Open this publication in new window or tab >>Particle Swarm Optimization for the Vehicle Routing Problem: A Survey and a Comparative Analysis
2018 (English)In: Handbook of Heuristics / [ed] Rafael Martí, Pardalos Panos, Dr. Mauricio G. C. Resende, Springer, 2018, p. 1-34Chapter in book (Refereed)
Abstract [en]

In the last few years, a number of books and survey papers devoted to the vehicle routing problem (VRP) or to its variants or to the methods used for the solution of one or more variants of the VRP have been published. Also, in these years, the field of swarm intelligence algorithms has a significant growth. One of the most important swarm intelligence algorithms is the particle swarm optimization (PSO). Although the particle swarm optimization was first published in 1995, it took around 10 years in order researchers to publish papers using a PSO algorithm for the solution of variants of the VRP. However, in the last 10 years, a lot of journal papers, conference papers, and book chapters have been published where a variant of VRP is solved using a PSO algorithm. Thus, it is significant to present a survey paper where a review and brief analysis of the most important of these papers will be given. This is the main focus of this chapter.

Place, publisher, year, edition, pages
Springer, 2018
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Logistics
Identifiers
urn:nbn:se:ltu:diva-66723 (URN)978-3-319-07153-4 (ISBN)978-3-319-07153-4 (ISBN)
Conference
Conference LOT 2014 : Logistics, optimization and transportation 01/09/2014 - 02/09/2014
Available from: 2017-11-23 Created: 2017-11-23 Last updated: 2018-04-11Bibliographically approved
Karakitsiou, A., Kourgiantakis, M., Mavrommati, A. & Migdalas, A. (2018). Regional efficiency evaluation by input-oriented data envelopment analysis of hotel and restaurant sector. Operational Research
Open this publication in new window or tab >>Regional efficiency evaluation by input-oriented data envelopment analysis of hotel and restaurant sector
2018 (English)In: Operational Research, ISSN 1109-2858, E-ISSN 1866-1505Article in journal (Refereed) Epub ahead of print
Abstract [en]

This paper analyses the efficiency of hotel and restaurant sector across all of the thirteen regions in Greece. For our purpose, DEA models were applied in order to evaluate the tourist efficiency and competitiveness of different regions in Greece. The application of this frontier method permits the calculation of efficiency scores based on a series of inputs (number of local units, number of employees and investments) and output (turnover). For the years, 2002–2013, with respectively constant and variable returns to scale models, the empirical analysis shows the differences in the efficiency performance of the Greek regions. More specifically, Attica and South Aegean can be regarded as “moving ahead” regions, whereas some other like, Thessaly, Central Macedonia, Central Greece and Epirus can be considered as “falling further” regions.

Place, publisher, year, edition, pages
Springer, 2018
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Logistics
Identifiers
urn:nbn:se:ltu:diva-68928 (URN)10.1007/s12351-018-0406-1 (DOI)
Available from: 2018-05-28 Created: 2018-05-28 Last updated: 2018-05-28
Marinakis, Y., Migdalas, A. & Sifaleras, A. (2017). A hybrid Particle Swarm Optimization: Variable Neighborhood Search Algorithm for Constrained Shortest Path Problems. European Journal of Operational Research, 261(3), 819-834
Open this publication in new window or tab >>A hybrid Particle Swarm Optimization: Variable Neighborhood Search Algorithm for Constrained Shortest Path Problems
2017 (English)In: European Journal of Operational Research, ISSN 0377-2217, E-ISSN 1872-6860, Vol. 261, no 3, p. 819-834Article in journal (Refereed) Published
Abstract [en]

In this paper, a well known NP-hard problem, the constrained shortest path problem, is studied. As efficient metaheuristic approaches are required for its solution, a new hybridized version of Particle Swarm Optimization algorithm with Variable Neighborhood Search is proposed for solving this significant combinatorial optimization problem. Particle Swarm Optimization (PSO) is a population-based swarm intelligence algorithm that simulates the social behavior of social organisms by using the physical movements of the particles in the swarm. A Variable Neighborhood Search (VNS) algorithm is applied in order to optimize the particles’ position. In the proposed algorithm, the Particle Swarm Optimization with combined Local and Global Expanding Neighborhood Topology (PSOLGENT), a different equation for the velocities of particles is given and a novel expanding neighborhood topology is used. Another issue in the application of the VNS algorithm in the Constrained Shortest Path problem is which local search algorithms are suitable from this problem. In this paper, a number of continuous local search algorithms are used. The algorithm is tested in a number of modified instances from the TSPLIB and comparisons with classic versions of PSO and with other versions of the proposed method are performed. Also, the results of the algorithm are compared with the results of a number of metaheuristic and evolutionary algorithms. The results obtained are very satisfactory and strengthen the efficiency of the algorithm.

National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Logistics
Identifiers
urn:nbn:se:ltu:diva-62564 (URN)10.1016/j.ejor.2017.03.031 (DOI)000401889300002 ()2-s2.0-85016465911 (Scopus ID)
Note

Validerad;2017;Nivå 2;2017-06-02 (andbra)

Available from: 2017-03-20 Created: 2017-03-20 Last updated: 2018-07-10Bibliographically approved
Marinakis, Y., Marinaki, M. & Migdalas, A. (2017). An Adaptive Bumble Bees Mating Optimization algorithm. Applied Soft Computing, 56, 13-30
Open this publication in new window or tab >>An Adaptive Bumble Bees Mating Optimization algorithm
2017 (English)In: Applied Soft Computing, ISSN 1568-4946, E-ISSN 1872-9681, Vol. 56, p. 13-30Article in journal (Refereed) Published
Abstract [en]

The finding of the suitable parameters of an evolutionary algorithm, as the Bumble Bees Mating Optimization (BBMO) algorithm, is one of the most challenging tasks that a researcher has to deal with. One of the most common used ways to solve the problem is the trial and error procedure. In the recent few years, a number of adaptive versions of every evolutionary and nature inspired algorithm have been presented in order to avoid the use of a predefined set of parameters for all instances of the studied problem. In this paper1, an adaptive version of the BBMO algorithm is proposed, where initially random values are given to each one of the parameters and, then, these parameters are adapted during the optimization process. The proposed Adaptive BBMO algorithm is used for the solution of the Multicast Routing Problem (MRP). As we would like to prove that the proposed algorithm is suitable for solving different kinds of combinatorial optimization problems we test the algorithm, also, in the Probabilistic Traveling Salesman Problem (PTSP) and in the Hierarchical Permutation Flowshop Scheduling Problem (HPFSP). Finally, the algorithm is tested in four classic benchmark functions for global optimization problems (Rosenbrock, Sphere, Rastrigin and Griewank) in order to prove the generality of the procedure. A number of benchmark instances for all problems are tested using the proposed algorithm in order to prove its effectiveness.

National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Logistics
Identifiers
urn:nbn:se:ltu:diva-61742 (URN)10.1016/j.asoc.2017.01.032 (DOI)000400031600002 ()2-s2.0-85012284307 (Scopus ID)
Note

Validerad; 2017; Nivå 2; 2017-02-23 (andbra)

Available from: 2017-01-31 Created: 2017-01-31 Last updated: 2018-07-10Bibliographically approved
Rogdakis, I., Marinaki, M., Marinakis, Y. & Migdalas, A. (2017). An Island Memetic Algorithm for Real World Vehicle Routing Problems (ed.). In: (Ed.), Evangelos Grigoroudis ; Michael Doumpos (Ed.), Operational Research in Business and Economics: 4th International Symposium and 26th National Conference on Operational Research, Chania, Greece, June 2015. Paper presented at International Symposium and 26th National Conference on Operational Research : 04/06/2015 - 06/06/2015 (pp. 205-223). Encyclopedia of Global Archaeology/Springer Verlag
Open this publication in new window or tab >>An Island Memetic Algorithm for Real World Vehicle Routing Problems
2017 (English)In: Operational Research in Business and Economics: 4th International Symposium and 26th National Conference on Operational Research, Chania, Greece, June 2015 / [ed] Evangelos Grigoroudis ; Michael Doumpos, Encyclopedia of Global Archaeology/Springer Verlag, 2017, p. 205-223Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, a new algorithm is presented which is applied to a real world Vehicle Routing Problem (VRP) of a provision company in the island of Crete in Greece. The company serves 116 customers located in Crete. This real world problem is solved effectively by a hybrid Island Memetic Algorithm (IMA) which employs Greedy Randomized Adaptive Search Procedure (GRASP) and Iterated Local Search (ILS). The proposed algorithm is also compared to five other approaches both on the real world problem and on classic benchmark instances from the literature. Methods such as GRASP, local search and Iterated Local Search (ILS) are employed as subroutines with certain probabilities in the algorithms. Furthermore, it is also demonstrated how premature convergence can be prevented by adopting specific strategy. Computational results show the superiority of the proposed hybrid Island Memetic Algorithm

Place, publisher, year, edition, pages
Encyclopedia of Global Archaeology/Springer Verlag, 2017
Series
Springer Proceedings in Business and Economics, ISSN 2198-7246
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Logistics
Identifiers
urn:nbn:se:ltu:diva-29767 (URN)10.1007/978-3-319-33003-7_10 (DOI)000405341000010 ()35774f9e-b603-42fb-9a33-adb4add543db (Local ID)978-3-319-33001-3 (ISBN)978-3-319-33003-7 (ISBN)35774f9e-b603-42fb-9a33-adb4add543db (Archive number)35774f9e-b603-42fb-9a33-adb4add543db (OAI)
Conference
International Symposium and 26th National Conference on Operational Research : 04/06/2015 - 06/06/2015
Note

Godkänd; 2016; 20160818 (andbra)

Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-07-10Bibliographically approved
Karakitsiou, A. & Migdalas, A. (2017). Locating facilities in a competitive environment (ed.). Paper presented at 4th World Congress on Global Optimization (WCGO), Gainesville, FL, February 22-25 2017. Optimization Letters, 11(5), 929-945
Open this publication in new window or tab >>Locating facilities in a competitive environment
2017 (English)In: Optimization Letters, ISSN 1862-4472, E-ISSN 1862-4480, Vol. 11, no 5, p. 929-945Article in journal (Refereed) Published
Abstract [en]

The research work dealing with the bi-level formulation of location problems is limited only to the competition among the locators, that is, it is supposed that either both the locator and the allocator are the same or the customer knows the optimality criterion of the locator and agrees passively with it. Customers’ preferences as well as externalities (such as road congestion, facility congestion, emissions etc) caused by the location decisions are either ignored or controlled by incorporating constraints in order to ensure the achievement of a predetermined target. However, this approach treats customers as irresolute beings. Thus, if, for example, the customers travel to the facilities to obtain the offered service, then there is no compulsion or intensive for them to attend the designated facility. This means that, once the facilities are open, what the locator wishes the customers to do may not coincide with their own wish and behavior. We suppose that the customers are involved in a Nash game in order to ensure what they conceive as the best level of services for themselves. In order to take into consideration the effects of such competition in the facilities location decisions we propose a bi-level programming approach to the problem.

National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Logistics
Identifiers
urn:nbn:se:ltu:diva-10217 (URN)10.1007/s11590-015-0963-7 (DOI)000401258300004 ()2-s2.0-84944704074 (Scopus ID)8fa78140-bf79-486b-b0ab-e64dc74e60c8 (Local ID)8fa78140-bf79-486b-b0ab-e64dc74e60c8 (Archive number)8fa78140-bf79-486b-b0ab-e64dc74e60c8 (OAI)
Conference
4th World Congress on Global Optimization (WCGO), Gainesville, FL, February 22-25 2017
Note

2017-05-12 (andbra);Konferensartikel i tidskrift

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Pei, J., Liu, X., Pardalos, P. M., Migdalas, A. & Yang, S. (2017). Serial-batching scheduling with time-dependent setup time and effects of deterioration and learning on a single-machine (ed.). Paper presented at 4th World Congress on Global Optimization (WCGO), Gainesville, FL, 22-25 February 2015. Journal of Global Optimization, 67(1-2), 251-262
Open this publication in new window or tab >>Serial-batching scheduling with time-dependent setup time and effects of deterioration and learning on a single-machine
Show others...
2017 (English)In: Journal of Global Optimization, ISSN 0925-5001, E-ISSN 1573-2916, Vol. 67, no 1-2, p. 251-262Article in journal (Refereed) Published
Abstract [en]

This paper deals with serial-batching scheduling problems with the effects of deterioration and learning, where time-dependent setup time is also considered. In the proposed scheduling models, all jobs are first partitioned into serial batches, and then all batches are processed on a single serial-batching machine. The actual job processing time is a function of its starting time and position. In addition, a setup time is required when a new batch is processed, and the setup time of the batches is time-dependent, i.e., it is a linear function of its starting time. Structural properties are derived for the problems of minimizing the makespan, the number of tardy jobs, and the maximum earliness. Then, three optimization algorithms are developed to solve them, respectively

National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Logistics
Identifiers
urn:nbn:se:ltu:diva-10552 (URN)10.1007/s10898-015-0320-5 (DOI)000392303600012 ()2-s2.0-84930535906 (Scopus ID)95fe12c9-71b6-45dc-b3a5-ae150a00c0f9 (Local ID)95fe12c9-71b6-45dc-b3a5-ae150a00c0f9 (Archive number)95fe12c9-71b6-45dc-b3a5-ae150a00c0f9 (OAI)
Conference
4th World Congress on Global Optimization (WCGO), Gainesville, FL, 22-25 February 2015
Note

Konferensartikel i tidskrift; 2017-02-16 (andbra)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Pei, J., Liu, X., Pardalos, P. M., Li, K., Fan, W. & Migdalas, A. (2017). Single-machine serial-batching scheduling with a machine availability constraint, position-dependent processing time, and time-dependent set-up time. Optimization Letters, 11(7), 1257-1271
Open this publication in new window or tab >>Single-machine serial-batching scheduling with a machine availability constraint, position-dependent processing time, and time-dependent set-up time
Show others...
2017 (English)In: Optimization Letters, ISSN 1862-4472, E-ISSN 1862-4480, Vol. 11, no 7, p. 1257-1271Article in journal (Refereed) Published
Abstract [en]

This article considers the single-machine serial-batching scheduling problem with a machine availability constraint, position-dependent processing time, and time-dependent set-up time. The objective of this problem is to make the decision of batching jobs and sequencing batches to minimize the makespan. To solve the problem, three cases of machine non-availability periods are considered, and the structural properties of the optimal solution are derived for each case. Based on these structural properties, an optimization algorithm is developed and an example is proposed to illustrate this algorithm

Place, publisher, year, edition, pages
Springer, 2017
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Logistics
Identifiers
urn:nbn:se:ltu:diva-59833 (URN)10.1007/s11590-016-1074-9 (DOI)000411114300006 ()2-s2.0-84986243115 (Scopus ID)
Note

Validerad;2017;Nivå 2;2017-09-20 (andbra)

Available from: 2016-10-19 Created: 2016-10-19 Last updated: 2018-07-10Bibliographically approved
Marinakis, Y., Marinaki, M. & Migdalas, A. (2016). A hybrid clonal selection algorithm for the location routing problem with stochastic demands (ed.). Paper presented at . Annals of Mathematics and Artificial Intelligence, 76(1-2), 121-142
Open this publication in new window or tab >>A hybrid clonal selection algorithm for the location routing problem with stochastic demands
2016 (English)In: Annals of Mathematics and Artificial Intelligence, ISSN 1012-2443, E-ISSN 1573-7470, Vol. 76, no 1-2, p. 121-142Article in journal (Refereed) Published
Abstract [en]

In this paper, a new formulation of the Location Routing Problem with Stochastic Demands is presented. The problem is treated as a two phase problem where in the first phase it is determined which depots will be opened and which customers will be assigned to them while in the second phase, for each of the open depots a Vehicle Routing Problem with Stochastic Demands is solved. For the solution of the problem a Hybrid Clonal Selection Algorithm is applied, where, in the two basic phases of the Clonal Selection Algorithm, a Variable Neighborhood Search algorithm and an Iterated Local Search algorithm respectively have been utilized. As there are no benchmark instances in the literature for this form of the problem, a number of new test instances have been created based on instances of the Capacitated Location Routing Problem. The algorithm is compared with both other variants of the Clonal Selection Algorithm and other evolutionary algorithms.

National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Logistics
Identifiers
urn:nbn:se:ltu:diva-7471 (URN)10.1007/s10472-014-9441-7 (DOI)000374449200008 ()2-s2.0-84913558445 (Scopus ID)5dc43253-6c74-461c-9df1-6ba8d09489df (Local ID)5dc43253-6c74-461c-9df1-6ba8d09489df (Archive number)5dc43253-6c74-461c-9df1-6ba8d09489df (OAI)
Note
Validerad; 2016; Nivå 2; 20141124 (athmig)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Marinakis, Y., Marinaki, M. & Migdalas, A. (2016). A Hybrid Discrete Artificial Bee Colony Algorithm for the Multicast Routing Problem (ed.). In: (Ed.), Giovanni Squillero, Paolo Burelli (Ed.), Applications of Evolutionary Computation: 19th European Conference, EvoApplications 2016, Porto, Portugal, March 30 - April 1, 2016, Proceedings. Paper presented at European Conference on the Applications of Evolutionary Computation : 30/03/2016 - 01/04/2016 (pp. 203-218). Encyclopedia of Global Archaeology/Springer Verlag
Open this publication in new window or tab >>A Hybrid Discrete Artificial Bee Colony Algorithm for the Multicast Routing Problem
2016 (English)In: Applications of Evolutionary Computation: 19th European Conference, EvoApplications 2016, Porto, Portugal, March 30 - April 1, 2016, Proceedings / [ed] Giovanni Squillero, Paolo Burelli, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 203-218Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, a new algorithm is proposed for the solution of the Multicast Routing Problem. The algorithm is based on the Artificial Bee Colony approach hybridized with Variable Neighborhood Search. The quality of the algorithm is evaluated with experiments conducted on suitably modified benchmark instances of the Euclidean Traveling Salesman Problem from the TSP library. The results of the algorithm are compared to results obtained by several versions of the Particle Swarm Optimization algorithm. The comparisons indicated the effectiveness of the new approach.

Place, publisher, year, edition, pages
Encyclopedia of Global Archaeology/Springer Verlag, 2016
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9597
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Logistics
Identifiers
urn:nbn:se:ltu:diva-26828 (URN)10.1007/978-3-319-31204-0_14 (DOI)2-s2.0-84961746308 (Scopus ID)015b0143-9b33-437d-be56-3a757a601f27 (Local ID)978-3-319-31203-3 (ISBN)978-3-319-31204-0 (ISBN)015b0143-9b33-437d-be56-3a757a601f27 (Archive number)015b0143-9b33-437d-be56-3a757a601f27 (OAI)
Conference
European Conference on the Applications of Evolutionary Computation : 30/03/2016 - 01/04/2016
Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-07-10Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0001-8473-3663

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